242 research outputs found

    Drawing explicit phylogenetic networks and their integration into SplitsTree

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    <p>Abstract</p> <p>Background</p> <p>SplitsTree provides a framework for the calculation of phylogenetic trees and networks. It contains a wide variety of methods for the import/export, calculation and visualization of phylogenetic information. The software is developed in Java and implements a command line tool as well as a graphical user interface.</p> <p>Results</p> <p>In this article, we present solutions to two important problems in the field of phylogenetic networks. The first problem is the visualization of explicit phylogenetic networks. To solve this, we present a modified version of the equal angle algorithm that naturally integrates reticulations into the layout process and thus leads to an appealing visualization of these networks. The second problem is the availability of explicit phylogenetic network methods for the general user. To advance the usage of explicit phylogenetic networks by biologists further, we present an extension to the SplitsTree framework that integrates these networks. By addressing these two problems, SplitsTree is among the first programs that incorporates <it>implicit </it>and <it>explicit </it>network methods together with standard phylogenetic tree methods in a graphical user interface environment.</p> <p>Conclusion</p> <p>In this article, we presented an extension of SplitsTree 4 that incorporates explicit phylogenetic networks. The extension provides a set of core classes to handle explicit phylogenetic networks and a visualization of these networks.</p

    On Three-Dimensional Space Groups

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    An entirely new and independent enumeration of the crystallographic space groups is given, based on obtaining the groups as fibrations over the plane crystallographic groups, when this is possible. For the 35 ``irreducible'' groups for which it is not, an independent method is used that has the advantage of elucidating their subgroup relationships. Each space group is given a short ``fibrifold name'' which, much like the orbifold names for two-dimensional groups, while being only specified up to isotopy, contains enough information to allow the construction of the group from the name.Comment: 26 pages, 8 figure

    NeighborNet: improved algorithms and implementation

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    NeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new simplified formulation of the first step, which aims at computing a circular ordering. We provide the first technical description of the second step, the estimation of split weights. We review the third step by constructing and drawing the network. Finally, we discuss how the networks might best be interpreted, review related approaches, and present some open questions

    Les Pavages d'Anges et de Diables

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    On utilise la méthode des symboles de Delaney pour classifier à l’aide de I’ordinateur, à homéomorphisme équivariant près, tous les pavages périodiques du plan dont les pavés peuvent être colories de noir et de blanc de telle manière que les pavés se partageant une arête soient de couleurs différentes, que le groupe de symétrie agisse de faGon transitive sur les pavés noirs, que tout pavé possède au moins trois arêtes et que de chaque sommet soient issues au moins trois arêtes.The method of Delaney symbols is used to classify by a computer program all periodic tilings of the Euclidean plane up to equivariant homeomorphisms for which the tiles can be coloured by black and white such that tiles sharing an edge have different colours, the symmetry group acts transitively on the black tiles, every tile has at least three edges and from every vertex at least three edges originate.Peer Reviewe

    Analysis of 16S rRNA environmental sequences using MEGAN

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    10.1186/1471-2164-12-S3-S1710th Int. Conference on Bioinformatics - 1st ISCB Asia Joint Conference 2011, InCoB 2011/ISCB-Asia 2011: Computational Biology - Proceedings from Asia Pacific Bioinformatics Network (APBioNet)12SUPPL. 3S1

    Computing galled networks from real data

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    Motivation: Developing methods for computing phylogenetic networks from biological data is an important problem posed by molecular evolution and much work is currently being undertaken in this area. Although promising approaches exist, there are no tools available that biologists could easily and routinely use to compute rooted phylogenetic networks on real datasets containing tens or hundreds of taxa. Biologists are interested in clades, i.e. groups of monophyletic taxa, and these are usually represented by clusters in a rooted phylogenetic tree. The problem of computing an optimal rooted phylogenetic network from a set of clusters, is hard, in general. Indeed, even the problem of just determining whether a given network contains a given cluster is hard. Hence, some researchers have focused on topologically restricted classes of networks, such as galled trees and level-k networks, that are more tractable, but have the practical draw-back that a given set of clusters will usually not possess such a representation

    CrossLink: visualization and exploration of sequence relationships between (micro) RNAs

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    CrossLink is a versatile tool for the exploration of relationships between RNA sequences. After a parametrization phase, CrossLink delegates the determination of sequence relationships to established tools (BLAST, Vmatch and RNAhybrid) and then constructs a network. Each node in this network represents a sequence and each link represents a match or a set of matches. Match attributes are reflected by graphical attributes of the links and corresponding alignments are displayed on a mouse-click. The distributions of match attributes such as E-value, match length and proportion of identical nucleotides are displayed as histograms. Sequence sets can be highlighted and visibility of designated matches can be suppressed by real-time adjustable thresholds for attribute combinations. Powerful network layout operations (such as spring-embedding algorithms) and navigation capabilities complete the exploration features of this tool. CrossLink can be especially useful in a microRNA context since Vmatch and RNAhybrid are suitable tools for determining the antisense and hybridization relationships, which are decisive for the interaction between microRNAs and their targets. CrossLink is available both online and as a standalone version at

    Phylogenetic analysis of condensation domains in NRPS sheds light on their functional evolution

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    <p>Abstract</p> <p>Background</p> <p>Non-ribosomal peptide synthetases (NRPSs) are large multimodular enzymes that synthesize a wide range of biologically active natural peptide compounds, of which many are pharmacologically important. Peptide bond formation is catalyzed by the Condensation (C) domain. Various functional subtypes of the C domain exist: An <sup>L</sup>C<sub>L </sub>domain catalyzes a peptide bond between two L-amino acids, a <sup>D</sup>C<sub>L </sub>domain links an L-amino acid to a growing peptide ending with a D-amino acid, a Starter C domain (first denominated and classified as a separate subtype here) acylates the first amino acid with a <it>β</it>-hydroxy-carboxylic acid (typically a <it>β</it>-hydroxyl fatty acid), and Heterocyclization (Cyc) domains catalyze both peptide bond formation and subsequent cyclization of cysteine, serine or threonine residues. The homologous Epimerization (E) domain flips the chirality of the last amino acid in the growing peptide; Dual E/C domains catalyze both epimerization and condensation.</p> <p>Results</p> <p>In this paper, we report on the reconstruction of the phylogenetic relationship of NRPS C domain subtypes and analyze in detail the sequence motifs of recently discovered subtypes (Dual E/C, <sup>D</sup>C<sub>L </sub>and Starter domains) and their characteristic sequence differences, mutually and in comparison with <sup>L</sup>C<sub>L </sub>domains. Based on their phylogeny and the comparison of their sequence motifs, <sup>L</sup>C<sub>L </sub>and Starter domains appear to be more closely related to each other than to other subtypes, though pronounced differences in some segments of the protein account for the unequal donor substrates (amino vs. <it>β</it>-hydroxy-carboxylic acid). Furthermore, on the basis of phylogeny and the comparison of sequence motifs, we conclude that Dual E/C and <sup>D</sup>C<sub>L </sub>domains share a common ancestor. In the same way, the evolutionary origin of a C domain of unknown function in glycopeptide (GP) NRPSs can be determined to be an <sup>L</sup>C<sub>L </sub>domain. In the case of two GP C domains which are most similar to <sup>D</sup>C<sub>L </sub>but which have <sup>L</sup>C<sub>L </sub>activity, we postulate convergent evolution.</p> <p>Conclusion</p> <p>We systematize all C domain subtypes including the novel Starter C domain. With our results, it will be easier to decide the subtype of unknown C domains as we provide profile Hidden Markov Models (pHMMs) for the sequence motifs as well as for the entire sequences. The determined specificity conferring positions will be helpful for the mutation of one subtype into another, e.g. turning <sup>D</sup>C<sub>L </sub>to <sup>L</sup>C<sub>L</sub>, which can be a useful step for obtaining novel products.</p
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